1. Field of the Invention
The present invention relates to a digital image processing technique, and more particularly to a method and apparatus for processing diagnostic images and detecting microcalcifications in a diagnostic image.
2. Description of the Related Art
Microcalcifications, which are small masses of mineral deposits such as calcium, can be scattered throughout the mammary glands, or may occur in clusters in breasts. Microcalcifications can indicate the presence of small benign cysts. However, microcalcifications can also be an early signal of breast cancer. Hence, medical problems can be diagnosed from mammography images by recognizing and detecting malignant microcalcifications.
A key problem with recognizing and detecting microcalcifications is the large number of false positives (FPs) that occur in vascular regions as the sensitivity of a calcification detection algorithm is increased. An example of an FP is a vascular region mistakenly identified as a microcalcification. A large number of spurious microcalcifications (FPs) are typically detected at the spot level. Such large number of FPs occur because the calcification detection algorithm can be easily confused by high frequency structure of vessels present in mammography images. An additional challenge to accurate detection and recognition of calcifications is the fact that signals generated by isolated calcifications are similar to signals generated by vessels. Since calcifications located within vessels are benign and therefore of no interest, an automated detection system that identifies calcifications in mammography images needs to rule out vascular regions. Difficulties in correctly identifying microcalcifications are compounded by the fact that edge profiles of microcalcifications are not always manifested with a strong contrast against the background, and may be discontinuous and exhibit high noise.
Disclosed embodiments of this application address these and other issues by using a method and an apparatus for generating a characteristic feature for candidate microcalcifications in breasts based on a Hessian matrix, to characterize topography of candidate microcalcifications. The method and apparatus use a Hessian peak characteristic feature for automated characterization and/or classification of candidate microcalcifications into true and false positives. The method and apparatus use the Hessian peak characteristic feature in CAD application for microcalcification detection and processing, with high levels of precision and specificity. The method and apparatus can be used for analysis and characterization of other structures in mammography images, and for analysis and characterization of various structures in diagnostic images other than mammograms. The method and apparatus can be used in other areas of image processing, for analysis and characterization of various structures in digital image data.